Principal component analysis for process monitoring in distributed system environment-Reference-Cited by-同舟云学术

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Principal component analysis for process monitoring in distributed system environment

Published:2019-04-29 Issue: Volume: Page:e5309
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Gao Shi‐wei¹^ORCID,Tian Ran²,Chen Peng¹

Affiliation:

1. College of Electric & Electronic EngineeringLanzhou Petrochemical Polytechnic Lanzhou China

2. College of Computer Science & EngineeringNorthwest Normal University Lanzhou China

Funder

Scientific research project of Lanzhou science and technology program

Scientific Research Projects for the Universities of Gansu Province

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5309

Reference30 articles.

1. Normalized relative RBC based minimum risk Bayesian decision approach for fault diagnosis of industrial process;Zheng Y;IEEE Trans Ind Electron,2016

2. Multivariate statistical process monitoring based on statistics pattern analysis;Wang J;Ind Eng Chem Res,2010

3. Statistical process monitoring: basics and beyond;Qin SJ;J Chemometr,2003

4. A new exponentially weighted moving average control charts for monitoring process dispersion;Haq A;Qual Reliab Eng Int,2015

5. Development and implementation of prospective outcome monitoring in a regional burns service using cumulative sum (CUSUM) techniques;Roberts G;Burns,2013

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1. Fault Diagnosis of an Industrial Chemical Process using Machine Learning Algorithms: Principal Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA);IOP Conference Series: Materials Science and Engineering;2024-04-01

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